The reference in this specification to any prior publication (or information derived from it), or to any matter which is known, is not, and should not be taken as an acknowledgment or admission or any form of suggestion that the prior publication (or information derived from it) or known matter forms part of the common general knowledge in the field of endeavour to which this specification relates.
Energy sustainability is a major challenge of the 21st century in the face of climate change. In order to reduce environmental impact such as greenhouse gas emissions, changes are required not only on the supply side of the energy chain but also on the demand side in reducing energy usage and improving energy efficiency.
Energy auditing is therefore often required to assess energy efficiency of buildings. Thermal infrared imaging is used for energy auditing assessments, in which energy flow is analysed for the purpose of identifying thermal infrared irregularities such as thermal infrared defects, air leakages, heat losses and thermal infrared bridges, energy wastage and energy inefficiency. Such energy audits rely on two-dimensional thermal infrared images of relevant parts of the building, such as furnaces, windows and other areas where energy inefficiencies are common.
A thermal infrared image sensor captures emitted or reflected thermal infrared radiation from objects and typically represents the thermal infrared data as a colour-mapped image, or a group of such images. The thermal infrared data is mapped to colour values to simplify visualisation of otherwise invisible thermal infrared radiation.
A problem with such energy auditing systems of the prior art is that they lack information on the location and orientation of objects with reference to each other, particularly across separate images. Generally, discrete objects are viewed separately, and are not considered in the context of other objects.
A further problem with such energy auditing systems of the prior art is that the thermal infrared imaging indirectly measures a temperature of an object by capturing thermal infrared radiation from a surface of the object. The captured thermal infrared radiation can, however, comprise a thermal infrared reflection from another object. The problem is exaggerated in windows and other objects having a “shiny” surface, as thermal infrared radiation is more likely to be reflected.
Thermal infrared imaging has also been demonstrated to be an effective tool for medical diagnosis. Thermal infrared cameras are able to discern abnormal temperature patterns, making them useful for medical diagnosis, treatment, examination and general health monitoring. Additionally, thermal infrared imaging is non-invasive, does not require skin contact and is radiation free. Medical applications of thermal infrared imaging include breast cancer detection, neonatal health monitoring, and neuro-imaging.
Medical thermal infrared imaging typically involves viewing a two-dimensional image of a person (or a part of a person). A problem with medical thermal infrared imaging of the prior art is that imaging artefacts are often present on edges of objects, objects far from the sensor, or areas where an angle of incidence is great. Similarly, it is often difficult for a medical practitioner to analyse a static two-dimensional thermal infrared image and compare thermal infrared images taken at different times, distances and angles
Certain systems have attempted to overcome some of these problems by using three-dimensional thermal infrared imaging. Such systems typically utilize an array of fixed-position thermal infrared sensors, which together are able to generate a three-dimensional thermal infrared model.
One problem with such systems is that they are costly, as several thermal infrared sensors are required. A further problem with such systems is that they are unable to map arbitrarily sized structures. This can, for example, result in a different configuration being required for full-body analysis than for analysis of a smaller body part such as a foot.
Yet a further problem of prior art medical thermal infrared imaging systems is that they may need to be repositioned and recalibrated at several locations around the patient in order to take multiple views. Calibration of these systems is also complex and generally requires the expertise of a trained engineer.
A general problem with thermal infrared imaging of the prior art is that the thermal infrared image data often varies depending on an angle and distance between the object and the camera during capture. This prevents quantitative and repeatable measurements unless monitoring is performed at the exact same position and angle with respect to the object at different times.
Accordingly, there is a need for an improved three-dimensional imaging method and system.